TY - GEN
T1 - Automated Pediatric Bone Age Assessment Using Convolutional Neural Networks
AU - Hsu, Feng Chiao
AU - Tsai, Meng Che
AU - Hsieh, Sun Yuan
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - Pediatric medicine widely uses bone age determination to assess skeletal maturity and identify developmental disorders early. However, manual assessment methods are subjective and lack consistency. To address this, we suggest using image preprocessing to isolate vital areas in hand X-rays and enhance features. We then enhance the Inception-V4 model to extract features from these images, integrating gender as a crucial reference. Our model, validated on a large dataset, demonstrates superior bone age prediction compared to prior methods. These automated models offer precise and reliable tools for clinical assessments, showing significant potential for practical application.
AB - Pediatric medicine widely uses bone age determination to assess skeletal maturity and identify developmental disorders early. However, manual assessment methods are subjective and lack consistency. To address this, we suggest using image preprocessing to isolate vital areas in hand X-rays and enhance features. We then enhance the Inception-V4 model to extract features from these images, integrating gender as a crucial reference. Our model, validated on a large dataset, demonstrates superior bone age prediction compared to prior methods. These automated models offer precise and reliable tools for clinical assessments, showing significant potential for practical application.
UR - https://www.scopus.com/pages/publications/85190700751
UR - https://www.scopus.com/pages/publications/85190700751#tab=citedBy
U2 - 10.1007/978-981-97-1714-9_19
DO - 10.1007/978-981-97-1714-9_19
M3 - Conference contribution
AN - SCOPUS:85190700751
SN - 9789819717132
T3 - Communications in Computer and Information Science
SP - 228
EP - 237
BT - Technologies and Applications of Artificial Intelligence - 28th International Conference, TAAI 2023, Proceedings
A2 - Lee, Chao-Yang
A2 - Lin, Chun-Li
A2 - Chang, Hsuan-Ting
PB - Springer Science and Business Media Deutschland GmbH
T2 - 28th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2023
Y2 - 1 December 2023 through 2 December 2023
ER -